Operationalizing Patient Experience Data as a System Feedback Asset in Learning Health Systems: Learnings From Model...

Learning Health Systems (LHS) offer a pathway to continuously improve care by integrating data and lived experience, yet few practical examples demonstrate how LHS can be operationalized in hospital settings in ways that embed the voices of patients and families. This manuscript describes how patient experience (PX) data are integrated into the design of a new model of care (MoC) that responds to both system demands and the realities of patients and families.

Researchers partnered with clinical leaders to integrate patient and family voices into the design of a new MoC using PX survey data, interviews with patients and families admitted to medicine units, and naturalistic walk-throughs of each medicine unit. Data collection explored care priorities, interactions with staff, physical environments, and reflections on positive and challenging aspects of care. Analysis followed a three-step iterative process: unit-level synthesis, cross-unit thematic comparison, and data integration.

In total, 390 patients participated in the PX survey and 19 patients/families participated in interviews. Patients situated their experiences within a health care system under strain, highlighting both strengths and gaps. Many expressed appreciation for nurses' compassion, but emotional support for fears, anxieties, and worries was inconsistent, particularly when staff were overstretched or transient. Long wait times for transport, procedures, or basic care needs were reported as sources of anxiety and diminished dignity. Naturalistic walk-throughs documented how crowding, noise, lighting, and wayfinding shaped patients' comfort and privacy.

This work provides a practical example of how an LHS approach can be operationalized by embedding the voices of patients and families into care redesign. Findings from the PX survey and interviews are directly shaping a new MoC at Trillium Health Partners (THP) that is evidence-informed and co-designed with patients and families, providing a practical example of how PX data can drive continuous, system-level learning.